INVESTIGATION INTO CURRENT EFFICIENCY FOR PULSE ELECTROCHEMICAL MACHINING OF NICKEL ALLOY

INVESTIGATION INTO CURRENT EFFICIENCY FOR PULSE ELECTROCHEMICAL MACHINING OF NICKEL ALLOY Yu Zhang, M.S. University of Nebraska, 2010 Adviser: Kamlakar P. Rajurkar Electrochemical machining (ECM) is a nontraditional manufacturing process that can machine difficult-to-cut materials. In ECM, material is removed by controlled electrochemical dissolution of an anodic workpiece in an electrochemical cell. ECM has extensive applications in automotive, petroleum, aerospace, textile, medical, and electronics industries. Improving current efficiency is a challenging task for any electro-physical or electrochemical machining processes. The current efficiency is defined as the ratio of the observed amount of metal dissolved to the theoretical amount predicted from Faraday’s law, for the same specified conditions of electrochemical equivalent, current, etc [1]. In macro ECM, electrolyte conductivity greatly influences the current efficiency of the process. Since there is a certain limit to enhance the conductivity of the electrolyte, a process innovation is needed for further improvement in current efficiency in ECM. Pulse electrochemical machining (PECM) is one such approach in which the electrolyte conductivity is improved by electrolyte flushing in pulse off-time. The aim of this research is to study the influence of major factors on current efficiency in a pulse electrochemical machining process in macro scale and to develop a linear regression model for predicting current efficiency of the process. An in-house designed electrochemical cell was used for machining nickel alloy (ASTM B435) by PECM. The effects of current density, type of electrolyte, and electrolyte flow rate, on current efficiency under different experimental conditions were studied. Results indicated that current efficiency is dependent on electrolyte, electrolyte flow rate, and current density. Linear regression models of current efficiency were compared with twenty new data points graphically and quantitatively. Models developed were close enough to the actual results to be reliable. In addition, an attempt has been made in this work to consider those factors in PECM that have not been investigated in earlier works. This was done by simulating the process by using COMSOL software. However, it was found that the results from this attempt were not substantially different from the earlier reported studies.

The Effects of High Pressure Processing on Peanut Sauce Inoculated with Salmonella

Recent Salmonella outbreaks have prompted the need for new processing options for peanut products. Traditional heating kill-steps have shown to be ineffective in lipid-rich matrices such as peanut products. High pressure processing is one such option for peanut sauce because it has a high water activity, which has proved to be a large contributing factor in microbial lethality due to high pressure processing. Four different formulations of peanut sauce were inoculated with a five strain Salmonella cocktail and high pressure processed. Results indicate that increasing pressure or increasing hold time increases log10 reductions. The Weibull model was fitted to each kill curve, with b and n values significantly optimized for each curve (p-value < 0.05). Most curves had an n parameter value less than 1, indicating that the population had a dramatic initial reduction, but tailed off as time increased, leaving a small resistant population. ANOVA analysis of the b and n parameters show that there are more significant differences between b parameters than n parameters, meaning that most treatments showed similar tailing effect, but differed on the shape of the curve. Comparisons between peanut sauce formulations at the same pressure treatments indicate that increasing amount of organic peanut butter within the sauce formulation decreases log10 reductions. This could be due to a protective effect from the lipids in the peanut butter, or it may be due to other factors such as nutrient availability or water activity. Sauces pressurized at lower temperatures had decreased log10 reductions, indicating that cooler temperatures offered some protective effect. Log10 reductions exceeded 5 logs, indicating that high pressure processing may be a suitable option as a kill-step for Salmonella in industrial processing of peanut sauces. Future research should include high pressure processing on other peanut products with high water activities such as sauces and syrups as well as research to determine the effects of water activity and lipid composition with a food matrix such as peanut sauces.

Improving IRT parameter estimates with small sample sizes: Evaluating the efficacy of a new data augmentation technique

The 3PL model is a flexible and widely used tool in assessment. However, it suffers from limitations due to its need for large sample sizes. This study introduces and evaluates the efficacy of a new sample size augmentation technique called Duplicate, Erase, and Replace (DupER) Augmentation through a simulation study. Data are augmented using several variations of DupER Augmentation (based on different imputation methodologies, deletion rates, and duplication rates), analyzed in BILOG-MG 3, and results are compared to those obtained from analyzing the raw data. Additional manipulated variables include test length and sample size. Estimates are compared using seven different evaluative criteria. Results are mixed and inconclusive. DupER augmented data tend to result in larger root mean squared errors (RMSEs) and lower correlations between estimates and parameters for both item and ability parameters. However, some DupER variations produce estimates that are much less biased than those obtained from the raw data alone. For one DupER variation, it was found that DupER produced better results for low-ability simulees and worse results for those with high abilities. Findings, limitations, and recommendations for future studies are discussed. Specific recommendations for future studies include the application of Duper Augmentation (1) to empirical data, (2) with additional IRT models, and (3) the analysis of the efficacy of the procedure for different item and ability parameter distributions.

Few-cycle attosecond pulse chirp effects on asymmetries in ionized electron momentum distributions

The momentum distributions of electrons ionized from H atoms by chirped few-cycle attosecond pulses are investigated by numerically solving the time-dependent Schrödinger equation. The central carrier frequency of the pulse is chosen to be 25 eV, which is well above the ionization threshold. The asymmetry (or difference) in the yield of electrons ionized along and opposite to the direction of linear laser polarization is found to be very sensitive to the pulse chirp (for pulses with fixed carrier-envelope phase), both for a fixed electron energy and for the energy-integrated yield. In particular, the larger the pulse chirp, the larger the number of times the asymmetry changes sign as a function of ionized electron energy. For a fixed chirp, the ionized electron asymmetry is found to be sensitive also to the carrier-envelope phase of the few-cycle pulse.